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Based on your comments I interpret your question as: "(1) What is the definition of the signal-to-noise-ratio (SNR) and (2) how do I determine the SNR for event-related potential (ERP) amplitudes in an EEG signal?". (1) Signal-to-noise-ratio (SNR) is a term often encountered in electrophysiology (e.g. EEG) and signal processing and can be loosely defined ...


5

An ERP is an Event Related Potential, making it inherently connected to an event. Having stimulus/response independent ERPs is thus impossible. There do exist potentials that seem to be stimulus independent, or at least vary in timing, but these are often the result of cognitive processes. These potentials are the result of Event Related (De-)Synchronization ...


5

The P300 wave is a positive deflection in the human event-related potential (ERP). A common experiment in which it is analyzed is the "oddball" paradigm, where a subject detects an occasional target stimulus in a regular train of standard stimuli. The P300 wave only occurs if the subject is actively engaged in the task of detecting the targets and its ...


4

Resting state EEG protocols already exist, but they do not focus on ERPs (thus solving your problem). You can assess coherence between pairs of electrodes (if you enter 'resting state EEG' into google scholar there will be a bunch of articles using this method) or you could instead go for the newer hidden Markov model separation into microstates (source). ...


3

The Lateralized Readiness Potential can be considered a later component of a more generalized Readiness Potential, i.e., an LRP would develop out of an RP. As such, RPs can be interesting if you want to determine the earliest point in time at which a movement plan "gets worked on" in the motor cortex. For reference, I recommend reading these sources and I ...


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You can buy the book in particular Chapter 18: Building an EEG study. There is also the PsychoPy forum with 50+ questions about EEG. You could also go to the lead developers OSF page and steal some code there from his EEG experiments.


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A collection of classic EEG experiments implemented in Python and Jupyter notebooks. Currently, all experiments are implemented for the Muse EEG device and using psychopy lib for stimulus presentation. Classification is made offline though. But I'll post very soon an online tutorial: https://github.com/NeuroTechX/eeg-notebooks/tree/master/notebooks


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I don't have experience with consumer grade EEG, but at fp1 and fp2 you should be able to measure the P3a response. Given the high impedance you will need a lot of trials, but the response is typically seen at fp1 and fp2 in research. http://www.sciencedirect.com/science/article/pii/S0168559798000331 For the Tp sites they are a bit posterior but you may ...


1

The question is quite vague, as it is unclear what the sample size is and whether OP is talking about an anecdotal experiment or the outcome of a well-powered statistical analysis. Moreover, there is mention of two conditions, but I fail to see what the difference is between the two. Assuming a normal sample size, I can say that the measured amplitudes of ...


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